Title :
Efficient Recommender Systems
Author :
Bergemann, D. ; Ozmen, Deran
Author_Institution :
Yale Univ., New Haven, CT
Abstract :
We study the efficient allocation of buyers in the presence of recommender systems. A recommender system affects the market in two ways: (i) it creates value by reducing product uncertainty for the customers and hence (ii) its recommendations can be offered as add-ons, which generates informational externalities. We investigate the impact of these factors on the efficient allocation of buyers across different products. We find that the efficient allocation requires that the seller with the recommender system has full market share. If the recommender system is sufficiently effective in reducing uncertainty, it is optimal to have some products to be purchased by a larger group of people than others. The large group consists of customers with flexible tastes
Keywords :
information filters; resource allocation; retail data processing; buyer allocation; product uncertainty; recommender systems; Recommender systems;
Conference_Titel :
E-Commerce Technology, 2006. The 8th IEEE International Conference on and Enterprise Computing, E-Commerce, and E-Services, The 3rd IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7695-2511-3
DOI :
10.1109/CEC-EEE.2006.42